This study aims to smartly assess the impact of tax policies and institutional pressures on corporate social responsibility performance and its economic and social outcomes in the context of Iran. The smart approach refers to the systematic application of advanced data analysis methods including structural equation modeling, system dynamics modeling, and machine learning-based clustering, which enable the discovery of non-linear relationships, feedback loops, and hidden patterns among firms. Given the relative stability of tax regulations in Iran, a mixed-methods approach (quantitative and qualitative) utilizing structured questionnaires and semi-structured interviews was employed. Data were collected from 385 respondents from companies listed on the Tehran Stock Exchange and non-listed firms in key industries such as oil and gas, petrochemicals, steel, and information technology. The results indicate that both favorable tax policies and institutional pressures significantly enhance corporate social responsibility performance, with institutional pressures having a stronger impact. Furthermore, corporate social responsibility performance is positively associated with economic outcomes (increased firm value and financial performance) and social outcomes (reduced crime rates and improved environmental behaviors). Cluster analysis identified three distinct groups of firms: smart leaders (information technology), moderate followers (steel and petrochemicals), and laggards (oil and gas). System dynamics analysis also revealed the existence of reinforcing feedback loops. This study, by providing a smart and integrated framework of the interaction between tax policies and institutional pressures, contributes to a deeper understanding of the role of corporate social responsibility in emerging markets, particularly Iran.